Optimization in container liner shipping

We will give an overview of several decision problem encountered in liner shipping. We will cover problems on the strategic, tactical and operational planning levels as well as problems that can be considered at two planning levels simultaneously. Furthermore, we will shortly discuss some related problems in terminals, geographical bottlenecks for container ships and provide an overview of operations research methods used in liner shipping problems. Thereafter, the decision problems will be illustrated using a case study for six Indonesian ports

Bunker Consumption Optimization in Liner Shipping: A Metaheuristic Approach

Taking into account increasing volumes of the international seaborne trade, liner shipping companies have to ensure efficiency of their operations in order to remain competitive. The bunker consumption cost constitutes a substantial portion of the total vessel operating cost and directly affects revenues of liner shipping companies. “Slow steaming” became a common strategy among ocean carriers to decrease vessel sailing speeds and reduce bunker consumption costs. However, decreasing vessel sailing speeds may require deployment of more vessels on a given shipping route to provide the agreed service frequency at each port of call. Several bunker consumption optimization methods were developed in the past to capture those conflicting decisions. This paper describes existing bunker consumption optimization methods, outlines their drawbacks, and proposes a new metaheuristic approach. Numerical experiments demonstrate efficiency of the suggested metaheuristic in terms of solution quality and computational time. DOI: 10.17762/ijritcc2321-8169.15065

Speed optimization and bunkering in liner shipping in the presence of uncertain service times and time windows at ports

Recent studies in maritime shipping have concentrated on environmental and economic impacts of ships. In this regard, fuel is considered as one of the important factors for such impacts. In particular, the sailing speed of the vessels affects the fuel consumption directly. In this study, we consider a speed optimization problem in liner shipping, which is characterized by stochastic port times and time windows. The objective is to minimize the total fuel consumption while maintaining the schedule reliability. We develop a dynamic programing model by discretizing the port arrival times to provide approximate solutions. A deterministic model is presented to provide a lower bound on the optimal expected cost of the dynamic model. We also work on the effect of bunker prices on the liner service schedule. We propose a dynamic programing model for bunkering problem. Our numerical study using real data from a European liner shipping company indicates that the speed policy obtained by proposed dynamic model performs significantly better than the ones obtained by benchmark methods. Moreover, our results show that making speed decisions considering the uncertainty of port times will noticeably decrease fuel consumption cost

Speed optimization and bunkering in liner shipping in the presence of uncertain service times and time windows at ports

© 2016 The Authors. Recent studies in maritime shipping have concentrated on environmental and economic impacts of ships. In this regard, fuel is considered as one of the important factors for such impacts. In particular, the sailing speed of the vessels affects the fuel consumption directly. In this study, we consider a speed optimization problem in liner shipping, which is characterized by stochastic port times and time windows. The objective is to minimize the total fuel consumption while maintaining the schedule reliability. We develop a dynamic programming model by discretizing the port arrival times to provide approximate solutions. A deterministic model is presented to provide a lower bound on the optimal expected cost of the dynamic model. We also work on the effect of bunker prices on the liner service schedule. We propose a dynamic programming model for bunkering problem. Our numerical study using real data from a European liner shipping company indicates that the speed policy obtained by proposed dynamic model performs signi cantly better than the ones obtained by benchmark methods. Moreover, our results show that making speed decisions considering the uncertainty of port times will noticeably decrease fuel consumption cost.This research is supported in part by EU FP7 project MINI-CHIP (Minimising Carbon Footprint in Maritime Shipping) under grant number PIAP-GA-2013-611693

Strategic maritime container transport design in oligopolistic markets

AbstractThis paper considers the maritime container assignment problem in a market setting with two competing firms. Given a series of known, exogenous demands for service between pairs of ports, each company is free to design a liner service network serving a subset of the ports and demand, subject to the size of their fleets and the potential for profit. The model is designed as a three-stage complete information game: in the first stage, the firms simultaneously invest in their fleet; in the second stage, they individually design their networks and solve the route assignment problem with respect to the transport demand they expect to serve, given the fleet determined in the first stage; in the final stage, the firms compete in terms of freight rates on each origin-destination movement. The game is solved by backward induction. Numerical solutions are provided to characterize the equilibria of the game

System Optimum and Collaborative Planning for Liner Shipping

There are multifarious academic research studies available concerning the optimization of a liner shipping company's benefit in terms of its individual behavior. The existing literature on alliance in liner shipping is still scarce, even though more and more carriers are collaborating with other carriers instead of getting improving their businesses by optimizing their own resources and information only. This research presents a unique methodology that a third party logistics firm can utilize to determine best schedules for liner shippers under total collaboration. A mixed integer linear programming (MIP) optimization model is developed to achieve the system optimum assuming total collaboration among partner shippers on the condition that a win-win solution is guaranteed for all participants. MIP optimization models are presented for a single carrier and for the overall system optimization under total collaboration. The system optimization model incorporates price strategy for equitable cost sharing. The price-strategy policy determines the additional price each liner company should charge other companies for shipping their demand. The methodology is verified for a three-carrier system using FICOTM Xpress Optimization Software to solve the MIP models. This study presents a practical membership mechanism to allocate resources among partner carriers to facilitate forming alliances most efficiently and equitably. A unique feature of the study is that the MIP models not only consider the shipping cost for the carriers based at a foreign port to US ports but it also includes the cost of shipment from a US port to the final MSA. Hence, the transportation network is integrated international network including global waterways and inland highways. The methodology can easily be expanded to include other cost elements or variations in the problem formulation